We present an electrolyte-gated graphene field effect transistor (GFET) nanosensor using aptamer for rapid, highly sensitive and specific detection of a lung cancer biomarker interleukin-6 (IL-6) with enhanced stability. The negatively charged aptamer folds into a compact secondary conformation upon binding with IL-6, thus altering the carrier concentration of graphene and yielding a detectable change in the drain-source current I. Aptamer has smaller size than other receptors (e.g. antibodies), making it possible to bring the charged IL-6 more closely to the graphene surface upon affinity binding, thereby enhancing the sensitivity of the detection. Thanks to the higher stability of aptamer over antibodies, which degrade easily with increasing storage time, consistent sensing performance was obtained by our nanosensor over extended-time (>24 h) storage at 25 °C. Additionally, due to the GFET-enabled rapid transduction of the affinity recognition to IL-6, detection of IL-6 can be achieved in several minutes (<10 min). Experimental results indicate that this nanosensor can rapidly and specifically respond to the change in IL-6 levels with high consistency after extended-time storage and a detection limit (DL) down to 139 fM. Therefore, our nanosensor holds great potential for lung cancer diagnosis at its early stage.
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http://dx.doi.org/10.1007/s10544-019-0409-6 | DOI Listing |
Int J Clin Oncol
January 2025
Translational Research Support Section, National Cancer Center Hospital East, Chiba, Japan.
Early cancer detection substantially improves the rate of patient survival; however, conventional screening methods are directed at single anatomical sites and focus primarily on a limited number of cancers, such as gastric, colorectal, lung, breast, and cervical cancer. Additionally, several cancers are inadequately screened, hindering early detection of 45.5% cases.
View Article and Find Full Text PDFXi Bao Yu Fen Zi Mian Yi Xue Za Zhi
January 2025
Department of Microbiology and Pathogenic Biology, Air Force Military Medical University, Xi'an 710032, China. *Corresponding authors, E-mail:
Objective The prevalence of drug-resistant Mycobacterium tuberculosis (Mtb) strains is exacerbating the global burden of tuberculosis (TB), highlighting the urgent need for new treatment strategies for TB. Methods The recombinant adenovirus vaccine expressing cyclic di-adenosine monophosphate (c-di-AMP) phosphodiesterase B (CnpB) (rAd-CnpB), was administered to normal mice via mucosal immunization, either alone or in combination with drug therapy, to treat Mtb respiratory infections in mice.Enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of antibodies in serum and bronchoalveolar lavage fluid (BALF).
View Article and Find Full Text PDFBackground: Lung cancer has high morbidity and mortality rates, which results in a poor prognosis. Cuproptosis is a novel cell death mechanism. The aim of this study was to examine the biological characteristics and clinical significance of genes associated with cuproptosis in lung adenocarcinoma (LUAD), and to understand the molecular mechanisms underlying the occurrence and progression of LUAD.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated associations between ECG encodings and ~1,600 Phecode-based diseases in three datasets separate from model development, and meta-analyzed the results.
View Article and Find Full Text PDFDeep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer risk prediction tasks using computed tomography (CT) scans. However, the lack of comprehensive comparison and validation of state-of-the-art (SOTA) models in practical settings limits their clinical application. This study aims to review and analyze current SOTA deep learning models for lung cancer risk prediction (malignant-benign classification).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!